- Work with large, complex datasets; solve difficult, non-routine analysis problems, applying advanced analytical methods as needed. Conduct end-to-end analysis that includes data gathering and requirements specification, processing, analysis, ongoing deliverables and presentations.
- Build and prototype analysis pipelines iteratively to provide insights at scale. Develop comprehensive understanding of data structures and metrics, advocating for changes where needed for both products development and sales activity.
- Make business recommendations with effective presentations
- Research and develop analysis, forecasting and optimization methods to improve the quality of user facing products
- MS degree in a quantitative discipline (e.g., statistics, operations research, bioinformatics, economics, computational biology, computer science, mathematics, physics, electrical engineering, industrial engineering) or equivalent practical experience.
- 10 years of relevant work experience in data analysis or related field (e.g., as a statistician / data scientist / computational biologist / bioinformatician).
- 5 years of people management / leadership experience
- Experience with statistical software (e.g., R, Python, MATLAB, pandas) and database languages (e.g., SQL).
- MSc degree or higher in a quantitative discipline (e.g., physics, statistics, operations research, bioinformatics, economics, computational biology, computer science, mathematics, physics, electrical engineering, industrial engineering).
- 5 years of directly relevant, tech industry work experience (e.g., as a bioinformatician / data scientist / statistician), including deep expertise and experience with statistical data analysis such as linear models, multivariate analysis, stochastic models, sampling methods.
- Applied experience with predictive analytics or machine learning.
- Experience articulating business questions and using mathematical techniques to arrive at an answer using available data. Experience translating analysis results into business recommendations.
- Demonstrated skills in selecting the right statistical tools given a data analysis problem.
- Demonstrated effective written and verbal communication skills.